在R中使用Aggregate（）和sum（）函数获得不同的结果 [英] Getting different results using aggregate() and sum() functions in R

问题描述

我正在尝试获取变量 prop.damage 和 crop.damage aggregate（）函数通过 STATE 变量通过$ c>：

I'm trying to get a summary data frame of the total quantities of the variables prop.damage and crop.damage by STATE variable using the aggregate() function in R with the following code:

stormdata$prop.damage <- with(stormdata, ifelse(PROPDMGEXP == 'K', (PROPDMG * 10^3), ifelse(PROPDMGEXP == 'M', (PROPDMG * 10^6), ifelse(PROPDMGEXP == 'B', (PROPDMG * 10^9), NA))))
stormdata$crop.damage <- with(stormdata, ifelse(CROPDMGEXP == 'K', (CROPDMG * 10^3), ifelse(CROPDMGEXP == 'M', (CROPDMG * 10^6), ifelse(CROPDMGEXP == 'B', (CROPDMG * 10^9), NA))))
damagecost <- with(stormdata, aggregate(x = prop.damage + crop.damage, by = list(STATE), FUN = sum, na.rm = TRUE))
damagecost <- damagecost[order(damagecost$x, decreasing = TRUE), ]

此处， PROPDMGEXP 和 CROPDMGEXP 变量用作 PROPDMG的乘数和 CROPDMG 数字变量。我的主要数据集是 stormdata 。

Here the PROPDMGEXP and CROPDMGEXP variables are used as a multiplier for the PROPDMG and CROPDMG numeric variables. My main data set is stormdata.

我得到以下信息：

> head(damagecost)
   Group.1            x
8       CA 120211639720
13      FL  27302948100
38      MS  14804212820
63      TX  12550131850
20      IL  11655920860
2       AL   9505473250

但是，例如，如果我为加利福尼亚州手动添加（ CA'）我明白了：

But, for example, If I do the addition "manually" for California ('CA') I get this:

> sum(stormdata$prop.damage[stormdata$STATE == 'CA'], na.rm = TRUE) + sum(stormdata$crop.damage[stormdata$STATE == 'CA'], na.rm = TRUE)
[1] 127115859410

我不明白为什么我会得到不同的结果。 / p>

I don't understand why I'm getting different results.

推荐答案

证明两个变量 prop.damage 和 crop.damage 中包含 NA 个值，而这些 NAs 会影响结果在 aggregate 函数中添加变量时。

Turns out that both variables prop.damage and crop.damage had NA values within them and those NAs were affecting the result when the variables were added in the aggregate function.

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